Abstract
The mobile fog computing (MFC) network that integrates unmanned aerial vehicles (UAV) fully exerts its advantages of flexible deployment, load balance, and rapid response. Under complex network environment, proposing a reasonable offloading model and according resource optimization of the MFC network is important to satisfy high-requirement offloading standard. In this paper, a multilevel MFC offloading model where UAV and fog nod undertake relay nodes and offloading computing nodes are established for computation-intensive and latency-critical tasks, considering heterogeneous network selection , dynamic channel quality and central cloud access . With the total system utility optimality function including reward function maximization as the goal, the MDP algorithm is applied to solve the best offloading decision of the computing task and the balanced load mode of the MFC network. Finally, the simulation section verifies the excellent performance of the proposed multilevel MFC offloading model in network resource utilization. Simulation results show that the model can optimize the relative position of service nodes in MFC network and ensure the offloading reliability of terminal equipment.
Highlights
In the era of rapid development of mobile communication technology, smart driving, smart home, unmanned detection, and other Internet of Things technologies are constantly changing lifestyles
To solve the problem of network migration and mobile fog computing offloading, in heterogeneous networks, this paper proposes an integrating unmanned aerial vehicles (UAV) multilevel MFC network offloading model (IMMFCM) based on the Markov decision process (MDP) algorithm
It can be seen that the total utility function of the multilevel mobile fog computing model proposed in this paper is the highest, which shows that the proposed model can realize the effectiveness and reliability of the network
Summary
In the era of rapid development of mobile communication technology, smart driving, smart home, unmanned detection, and other Internet of Things technologies are constantly changing lifestyles. In the three-level fog computing network, Xianglin et al [12] apply three decision algorithms to solve a joint resource optimization problem, which is formulated that takes the weighted sum of energy consumption and delay experienced by tasks as the objective function. To solve the problem of network migration and mobile fog computing offloading, in heterogeneous networks, this paper proposes an integrating UAV multilevel MFC network offloading model (IMMFCM) based on the MDP algorithm. Considering the size of the task itself, the model applies the MDP algorithm to obtain the best resource optimization and offloading decision by an iterative method (iii) Considering the heterogeneous network, this model analyzes the network selection of mobile terminals in the MFC network during migration and obtains the best offloading strategy to realize low-cost network connection
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